Latest Documents

This report outlines a new methodology and provides a first exploratory analysis of technologies and applications that are at the core of recent advances in AI. Using AI-related keywords and technology classes, the study identifies AI-related patents protected in the United States in 2000-18. Among those, 'core' AI patents are selected based on their counts of AI-related forward citations. The analysis finds that, compared to other (AI and non-AI) patents, they are more original and general, and tend to be broader in technological scope. Technologies related to general AI, robotics, computer/image vision and recognition/detection are consistently listed among core AI patents, with autonomous driving and deep learning having recently become more prominent. Finally, core AI patents tend to spur innovation across AI-related domains, although some technologies – likely AI applications, such as autonomous driving or robotics – appear to increasingly contribute to developments in their own field.

First adopted in 1980, the OECD Privacy Guidelines are the first internationally agreed-upon set of privacy principles. They are framed in concise, technology-neutral language and have significantly influenced legislation and policy in OECD member countries and beyond. In 2018, the OECD initiated a comprehensive review of the Privacy Guidelines, which included a survey of Adherents, an ad hoc group of experts, and several workshops to explore the main challenges for privacy and personal data protection in an ever-evolving digital environment. This report presents the review's findings, confirming the continued importance and relevance of the Privacy Guidelines. However, it also highlights persistent and emerging implementation challenges and provides recommendations for addressing them.

The OECD AI Principles call for AI actors to be accountable for the proper functioning of their AI systems in accordance with their role, context, and ability to act. Likewise, the OECD Guidelines for Multinational Enterprises aim to minimise adverse impacts that may be associated with an enterprise’s operations, products and services. To develop ‘trustworthy’ and ‘responsible’ AI systems, there is a need to identify and manage AI risks. As calls for the development of accountability mechanisms and risk management frameworks continue to grow, interoperability would enhance efficiency and reduce enforcement and compliance costs. This report provides an analysis of the commonalities of AI risk management frameworks. It demonstrates that, while some elements may sometimes differ, all the risk management frameworks analysed follow a similar and sometimes functionally equivalent risk management process.

Responsible science communication is crucial for fostering public trust in science and promoting evidence-based policymaking. However, in an evolving landscape shaped by the digital transformation and complex crises like the COVID-19 pandemic, science communication faces new challenges including widespread mis- and disinformation. To address these challenges, science communicators should follow key principles for responsible science communication including transparency, inclusivity, integrity, accountability, freedom and autonomy, and timeliness. Policymakers in turn are encouraged to promote these principles, invest in science communication capacity, establish crisis communication structures, support scientists in public communication, and promote scientific and digital literacy.

In 2019, the OECD Council adopted the Recommendation on Artificial Intelligence (the 'OECD AI Principles'). These include five values-based principles and five recommendations for OECD countries and adhering partner economies to promote responsible and trustworthy AI policies. This report takes stock of initiatives launched by countries worldwide to implement the OECD AI Principles which were reported to the OECD.AI Policy Observatory as of May 2023. It provides an overview of national AI strategies, including their oversight and monitoring bodies, expert advisory groups, as well as their monitoring and evaluation frameworks. It also discusses the various regulatory approaches that countries are adopting to ensure AI trustworthiness, such as ethics frameworks, AI-specific regulations, and regulatory sandboxes. Additionally, the report offers policy examples for each of the ten OECD AI Principles to facilitate cross-learning among policymakers.

The OECD Privacy Guidelines are the first internationally agreed-upon set of privacy principles and are recognized as the global minimum standard for privacy and data protection. They are a solid foundation for building effective protection and trust for individuals, and also for developing common international approaches to transborder data flows. Since their adoption, they have influenced legislation and policy in OECD countries and beyond. This document reproduces the two existing explanatory memoranda that accompany the OECD Privacy Guidelines. The first, published in 1980, was developed alongside the original version of the OECD Privacy Guidelines to help in their interpretation and application. The supplementary Explanatory Memorandum was developed to provide context and rationale for the revisions to the OECD Privacy Guidelines made in 2013.

Artificial intelligence (AI) offers tremendous benefits but also poses risks. Some of these risks have materialised into what are known as 'AI incidents'. Due to the widespread use of AI in various sectors, a surge in such incidents can be expected. To effectively monitor and prevent these risks, stakeholders need a precise yet adaptable definition of AI incidents. This report presents research and findings on terminology and practices related to incident definitions, encompassing both AI-specific and cross-disciplinary contexts. It establishes a knowledge base for identifying commonalities and encouraging the development of AI-specific adaptations in the future.

Stimulus packages adopted following the COVID-19 pandemic – such as the US Inflation Reduction Act and NextGenerationEU - have been presented as an opportunity to 'build back better' and accelerate the transition to a low-carbon economy while re-igniting the economy. But this revival of industrial policy has also raised concerns about the potential for a global green subsidy war. OECD analysed funding measures worth USD 1.3 trillion announced around the world in 2020-21 to support development and diffusion of low-carbon technologies. These measures can trigger substantial greenhouse gas emissions reductions while boosting the growth of the clean tech sector in all regions and reducing dependence over fossil fuel imports. This policy brief summarises key findings from our analysis and offers additional recommendations to policymakers.